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A Comparative Study of Single Trait and Multi-Trait Genomic Selection

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Title A Comparative Study of Single Trait and Multi-Trait Genomic Selection
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Creator Neeraj Budhlakoti
Dwijesh Chandra Mishra
Rai Anil
Lal S. B
K. K. Chaturvedi
Kumar Rajeev Ranjan
 
Subject STGS
LASSO
GS
 
Description Not Available
In recent years of animal and plant breeding research, genomic selection (GS) became a choice for selection of appropriate candidate for breeding as it significantly contributes to enhance the genetic gain. Various studies related to GS have been carried out in the recent past. These studies were mostly confined to single trait. Although GS methods based on single trait have not performed very well in cases like pleiotropy, missing data and when the trait under study has low heritability. Gradually, some studies were carried out to explore the possibility of methods for GS based on multiple traits in the view of overcoming the above-mentioned problems in the method of single-trait GS (STGS). Currently, multi-trait-based GS methods are getting importance as it exploits the information of correlated structure among response. In this study, we have compared various methods related to STGS, such as stepwise regression, ridge regression, least absolute shrinkage and selection operator (LASSO), Bayesian, best linear unbiased prediction, and support vector machine, and multi-trait-based GS methods, such as multivariate regression with covariance estimation, conditional Gaussian graphical models, mixed model, and LASSO. In almost all cases, multi-trait-based methods are found to be more accurate. Based on the results of this study, it may be concluded that multi-trait-based methods have great potential to increase genetic gain as they utilize the correlation among the response variable as extra information, which contributes to estimate breeding value more precisely. This study is a comprehensive review of the methods of GS right from single trait to multiple traits and comparisons among these two classes.
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Date 2023-03-02T09:23:49Z
2023-03-02T09:23:49Z
2019-04-01
 
Type Research Paper
 
Identifier Not Available
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http://krishi.icar.gov.in/jspui/handle/123456789/76543
 
Language English
 
Relation Not Available;
 
Publisher Not Available